#!/usr/bin/env python3
"""Generate manuscript tables solely from saved numerical summaries."""
import argparse
import json
from pathlib import Path

ROOT = Path(__file__).resolve().parent
RESULTS = ROOT / 'experiment' / 'results'
TABLES = ROOT / 'tables'


def read(name):
    return json.loads((RESULTS / name / 'summary.json').read_text())


def sci(value, precision=4):
    if value == 0:
        return '$0$'
    mantissa, exponent = f'{value:.{precision}e}'.split('e')
    return f'${mantissa}\\times10^{{{int(exponent)}}}$'


def write_table(name, alignment, header, rows):
    lines = [r'\begingroup', r'\small', r'\setlength{\tabcolsep}{4pt}',
             r'\begin{tabular}{' + alignment + '}', r'\toprule',
             ' & '.join(header) + r'\\', r'\midrule']
    lines.extend(' & '.join(row) + r'\\' for row in rows)
    lines.extend([r'\bottomrule', r'\end{tabular}', r'\endgroup', ''])
    (TABLES / name).write_text('\n'.join(lines))


def main():
    global RESULTS, TABLES
    parser = argparse.ArgumentParser(description=__doc__)
    parser.add_argument("--results", default="experiment/results")
    parser.add_argument("--output", default="tables")
    args = parser.parse_args()
    RESULTS = (ROOT / args.results).resolve()
    TABLES = (ROOT / args.output).resolve()
    TABLES.mkdir(parents=True, exist_ok=True)
    conv = read('convergence')['rows']
    write_table('convergence_table.tex', 'rrrrrr',
                ['$J$', '$h$', r'$L_h^2$', r'$H_h^1$', 'Time difference', 'Order'],
                [[str(r['sites']), f"{r['h']:.5f}", sci(r['max_l2'], 3),
                  sci(r['max_h1'], 3), sci(r['max_time_difference_l2'], 3),
                  '--' if r['order_h1'] is None else f"{r['order_h1']:.3f}"] for r in conv])
    speeds = read('spectroscopy')['speeds']
    write_table('speed_table.tex', 'rcrrr',
                ['$J$', 'Branch', '$m_{\\rm fit}^2$', '$c_{\\rm fit}$', 'Max. rel. error'],
                [[str(r['sites']), '$' + r['branch'] + '$', f"{r['mass_sq_fit']:.8f}",
                  f"{r['speed_fit']:.8f}", sci(r['max_relative_continuum_error'], 3)] for r in speeds])
    coll = read('collision')
    principal = next(r for r in coll['runs'] if r['label'] == coll['principal_label'])
    rows = sorted((r for r in coll['runs'] if r['sites'] == principal['sites']
                   and r['content'] == 'both' and not r['linear'] and r['epsilon'] >= 0),
                  key=lambda r: r['epsilon'])
    cross = {(r['sites'], r['epsilon']): r['max_v_excess'] for r in coll['cross_excess']}
    write_table('epsilon_table.tex', 'rrrr',
                [r'$\varepsilon$', r'$\max\|v\|_h$', r'$\max E_{v,\mathrm{quad}}$', r'$\max C_v$'],
                [[f"{r['epsilon']:.3f}", sci(r['max_v_l2']), sci(r['max_v_quadratic_energy']),
                  sci(cross.get((r['sites'], r['epsilon']), 0.0))] for r in rows])
    write_table('collision_refinement_table.tex', 'crrr',
                ['Grid pair', 'Full field', '$v$ field', '$v$ excess field'],
                [[f"{r['coarse']} / {r['fine']}", sci(r['max_field_difference']),
                  sci(r['max_v_difference']), sci(r['max_v_cross_excess_difference'])]
                 for r in coll['refinement']])
    source = read('source_check')['rows']
    write_table('source_response_table.tex', 'rrr',
                [r'$\varepsilon$', r'$\max\|v_\varepsilon/\varepsilon-v_1\|_h$',
                 r'$\max\|v_{h,\varepsilon}-v_\varepsilon\|_h$'],
                [[f"{r['epsilon']:.3f}", sci(r['max_v_over_epsilon_minus_v1_l2']),
                  sci(r['max_automaton_v_minus_continuum_v_l2'])] for r in source])
    print('Generated 5 manuscript tables from saved summaries.')


if __name__ == '__main__':
    main()